AI Integration

AI Integrated Chatbot

TiCON brings first Hardware integrated multilingual chatbot (Bengali, English, Korean, Japanese and it can be extended to any other languages), we intent to utilize full power of Big Data, NLP, ML & Speech Recognition technology.

Mobile Application

Technology We Used

Machine Learning (ML)

Natural Language Proccessing(NLP)

Our Own Algorithm

Speach Recognition(STT & TTS)

What We Achieved

TiCON brings first Hardware integrated chatbot, in Bengali, we intent to utilize full power of Big Data, NLP, ML & Speech Recognition technology.

Day-To-Day Task

We can now schedule alarm, schedule/reminder, ask our bot to search anything for us, call to any contact or any number, Open any other app etc.

Conversation

When making small talk with THEIA, bot can communicate with you with some real nice response. It can be enjoyable at the same time it can be very informative for you.

Multilingual

THEIA is multilingual. Currently it works on Bengali, English, Japanese & Korean. And have the ability to expand to any other language.

First 3D Model & Hardware

THEIA is first bot integrated with hardware based 3D model in Bangladesh & one of the few in the world. We are using Android box for hosting the 3D model.

Working on Big Data

We recently started taking public input while making a conversation, as our plan to work with Big Data & NLP. The more data we have, the better THEIA will be.

The Process We Folllow

Machine Learning

- Utilize Apache SparkML

- Use JAVA wrapper for Android

- Initial data inventory for Machine Learning

The AI Part

- Grow data inventory based on conversation & user input

- Unsupervised model for auto learning from input

App (Android & iOS)

- Android app for frontend functionality/user engagement with ML

- Android connects with Python/Django backend

WORKFLOW

01

User Calls

User calls to our contact center

02

We Record

We record all conversation for our future ML/AI implementation

03

Convert

We convert all voice conversation to text

04

Save To DB

Then we save our all conversation to our database

05

Implement ML

We implement ML to all recorded conversation, for pattern understanding

06

Implement AI

Then we implement AI to auto answer user queries using our ML technology

07

Deliver

We can deliver all support question answers automatically, given there is enough data & pattern

08

TTS

Text to speech implementation can also be done following same protocol